rsgedgesByGene-methods: Extract the reduced edges and their ranges from a...

In Bioconductor/SplicingGraphs: Create, manipulate, visualize splicing graphs, and assign RNA-seq reads to them

Extract the reduced edges and their ranges from a SplicingGraphs object

Description

rsgedgesByGene and rsgedgesByTranscript are analog to sgedgesByGene and sgedgesByTranscript, but operate on the reduced splicing graphs, that is, the graphs in SplicingGraphs object x are reduced before the edges and their ranges are extracted. The reduced graphs are obtained by removing the uninformative nodes from it. See Details section below.

rsgedges extracts the edges of the reduced splicing graph of a given gene from a SplicingGraphs object.

rsgraph extracts the reduced splicing graph for a given gene from a SplicingGraphs object, and returns it as a plottable graph-like object.

Usage

rsgedgesByGene(x, with.hits.mcols=FALSE, keep.dup.edges=FALSE)

rsgedgesByTranscript(x, with.hits.mcols=FALSE)

rsgedges(x)

rsgraph(x, tx_id.as.edge.label=FALSE, as.igraph=FALSE)

## Related utility:
uninformativeSSids(x)

Arguments

x	A SplicingGraphs object. Must be of length 1 for rsgedges, rsgraph, and uninformativeSSids.
with.hits.mcols	Whether or not to include the hits metadata columns in the returned object. See ?countReads for more information.
keep.dup.edges	Not supported yet.
tx_id.as.edge.label	Whether or not to use the transcript ids as edge labels.
as.igraph	TODO

Details

TODO: Explain graph reduction.

Value

For rsgedgesByGene: A GRangesList object named with the gene ids and where the reduced splicing graph edges are grouped by gene.

TODO: Explain values returned by the other function.

Author(s)

H. Pagès

See Also

This man page is part of the SplicingGraphs package. Please see ?`SplicingGraphs-package` for an overview of the package and for an index of its man pages.

Examples

## ---------------------------------------------------------------------
## 1. Make SplicingGraphs object 'sg' from toy gene model (see
##    '?SplicingGraphs')
## ---------------------------------------------------------------------
example(SplicingGraphs)
sg

## 'sg' has 1 element per gene and 'names(sg)' gives the gene ids.
names(sg)

## ---------------------------------------------------------------------
## 2. rsgedgesByGene()
## ---------------------------------------------------------------------
edges_by_gene <- rsgedgesByGene(sg)
edges_by_gene
## 'edges_by_gene' has the length and names of 'sg', that is, the names
## on it are the gene ids and are guaranteed to be unique.

## Extract the reduced edges and their ranges for a given gene:
edges_by_gene[["geneA"]]
## Note that edge with global reduced edge id "geneA:1,2,4,5" is a mixed
## edge obtained by combining together edges "geneA:1,2" (exon),
## "geneA:2,4" (intron), and "geneA:4,5" (exon), during the graph
## reduction.

stopifnot(identical(edges_by_gene["geneB"], rsgedgesByGene(sg["geneB"])))

## ---------------------------------------------------------------------
## 3. sgedgesByTranscript()
## ---------------------------------------------------------------------
#edges_by_tx <- rsgedgesByTranscript(sg)  # not ready yet!
#edges_by_tx

## ---------------------------------------------------------------------
## 4. rsgedges(), rsgraph(), uninformativeSSids()
## ---------------------------------------------------------------------
plot(sgraph(sg["geneB"]))
uninformativeSSids(sg["geneB"])

plot(rsgraph(sg["geneB"]))
rsgedges(sg["geneB"])

## ---------------------------------------------------------------------
## 5. Sanity checks
## ---------------------------------------------------------------------
## TODO: Do the same kind of sanity checks that are done for sgedges()
## vs sgedgesByGene() vs sgedgesByTranscript() (in man page for sgedges).

Bioconductor/SplicingGraphs documentation built on Nov. 3, 2024, 8:11 a.m.